{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dots1 = np.random.uniform(0.0, 0.5, size = (100, 2) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "dots2 = np.random.uniform(0.4, 1.5, size = (100, 2) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.savetxt('./matplot_test.txt',dots1, fmt =\"%f %f\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f9571f24cd0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(dots1[:,0], dots1[:,1])\n",
    "plt.scatter(dots2[:,0], dots2[:,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 2)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dots1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f9538638790>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWoAAAD4CAYAAADFAawfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAOdklEQVR4nO3dbYxc5XnG8evCawyGCFvxtHVx3I0UNRJF4aUjyykVSqFUtInMh6DKlWhLpGoVEuWlLYGmkWnTL0nVpkpfJKhFW9EmIQmOaVwrSUGyI5IPdTTGNi8xbYxjErsEDwkvwVCbXd/9MGeczXpm5+x6zsw9O/+fNGJmz7Oz9+OHvfbeZ+bscUQIAJDXecMuAAAwP4IaAJIjqAEgOYIaAJIjqAEguYkqnnTNmjUxOTlZxVMDwJK0d+/e5yOi1ulYJUE9OTmpRqNRxVMDwJJk+5lux9j6AIBFCkl/Jen/Kv46BDUALNIOSXdI+seKvw5BDQCLEJJuL+7/uartqglqAFiEHZJ+UNx/XdV21QQ1ACxQu5t+pXh8QtV21QQ1ACzQ7G66rcquulRQ2/5D20/afsL2/bYvqKgeAEhtbjfdVmVX3TOobV8q6YOS6hFxuaRlkjZXUAsApNepm26rqqsuu/UxIelC2xOSVkr63wpqAYDUunXTbVV11T2DOiKOSfprSd+T9KyklyLioT7XAQDpzddNt1XRVZfZ+lgt6SZJb5b085Iusn1Lh3FTthu2G81ms89lAsBw9eqm26roqstsffy6pO9GRDMiXpe0XdKvzB0UEVsjoh4R9Vqt498VAYCRVaabbut3V10mqL8naaPtlbYt6XpJB/tYAwCkVrabbut3V11mj3qPpG2SHpX0ePE5W/v09QEgvYV002397KpdxVXI6/V68GdOASwFIekXJR1axOeuUusdGGVOPLG9NyLqnY5xZiIAzGMx3XRbv7pqghoAuljo3vRc/dqrJqgBoIsdkrpedqWkVyXdc47PUcmluABgKTgpaUMfnsfn+PkENQB08dvFbdjY+gCA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5HoGte232t4/6/ay7Q8PojgAQImL20bEf0u6UpJsL5N0TNKDFdcFACgsdOvjeklPR8QzVRQDADjbQoN6s6T7Ox2wPWW7YbvRbDbPvTIAgKQFBLXt8yVtkvRAp+MRsTUi6hFRr9Vq/aoPAMbeQjrq35T0aEQ8V1UxAICzLSSof0ddtj0AANUpFdS2L5J0g6Tt1ZYDAJir59vzJCkiTkh6Y8W1AAA64MxEAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5AhqAEiOoAaA5EoFte1VtrfZfsr2Qdtvr7owAEDLRMlxfyvpaxFxs+3zJa2ssCYAwCw9g9r2JZKulXSrJEXEKUmnqi0LANBWZuvjzZKakv7F9j7b99q+aO4g21O2G7YbzWaz74UCwLgqE9QTkq6WdHdEXCXphKQ/mTsoIrZGRD0i6rVarc9lAsD4KhPURyUdjYg9xeNtagU3AGAAegZ1RPxA0vdtv7X40PWSvl1pVQCAM8q+6+MDkj5bvOPjsKT3VFcSAGC2UkEdEfsl1SuuBQDQAWcmAkByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByBDUAJEdQA0ByE2UG2T4i6ceSZiRNR0S9yqIAAD9RKqgLvxYRz1dWCQCgI7Y+ACC5skEdkh6yvdf2VJUFAQB+Wtmtj1+NiGO2f0bSw7afiohHZg8oAnxKktavX9/nMgFgfJXqqCPiWPHf45IelLShw5itEVGPiHqtVutvlQAwxnoGte2LbL+hfV/Sb0h6ourCAAAtZbY+flbSg7bb4z8XEV+rtCoAwBk9gzoiDku6YgC1AAA64O15AJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUAJAcQQ0AyRHUwAjZt0/65CeHXQUGjaAGRshtt0kf+5h06NCwK8EglQ5q28ts77O9s8qCAHT2jW9Ijz8u2a2wxvhYSEf9IUkHqyoEwPw+8hHp1VelmRlpxw666nFSKqhtr5P0Tkn3VlsOgE7a3XTb9DRd9Tgp21F/WtIdkk53G2B7ynbDdqPZbPalOAAt7W66bXqarnqc9Axq2++SdDwi9s43LiK2RkQ9Iuq1Wq1vBQLjbm433UZXPT7KdNTXSNpk+4ikz0u6zvZnKq0KwBlzu+k2uurx0TOoI+KjEbEuIiYlbZa0KyJuqbwyAF276Ta66vEwMewCAHT3qU+1wviSSzofn5mRtm2TXnhBWr16sLVhcBYU1BHxdUlfr6QSAGe5+27p6NH5x6xYIa1aNZh6MBx01EBia9e2bhhvnEIOAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEENAMkR1ACQHEGNeX3im5/QnqN7hl0GMNZ6BrXtC2x/y/YB20/a/vggCsPwHX7hsLbs2qL37nyvImLY5QBjq0xHfVLSdRFxhaQrJd1oe2O1ZSGDLbu2yLa+86PvaNd3dw27HGBs9QzqaHmleLi8uNFeLXGHXzis7U9t1/TpaZ14/YRuf+h2umpgSErtUdteZnu/pOOSHo6IszYtbU/ZbthuNJvNfteJAduya4umT0+feUxXDQxPqaCOiJmIuFLSOkkbbF/eYczWiKhHRL1Wq/W7TgzQ7G66ja4aGJ4FvesjIl6UtFvSjdWUgwzu2n2XTs2cOuvjjx1/TLuP7B5CRcB4m+g1wHZN0usR8aLtCyXdIOkvK68MQ3Pt+mu1cvnKsz5uWasvWD2EioDx1jOoJa2VdJ/tZWp14F+MiJ3VloVhmqpPaUpTwy4DQKFnUEfEY5KuGkAtAIAOODMRAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJIjqAEgOYIaAJLrGdS232R7t+1v237S9ocqrejEiUqfHgBGTZmOelrSH0fEZZI2Snq/7csqqebAAWnNGunIkUqeHgBGUc+gjohnI+LR4v6PJR2UdGkl1dx5p3TqlHTXXZU8PQCMogXtUduelHSVpD19r+TAAemRR6TTp6UHHpCeeabvXwIARlHpoLZ9saQvSfpwRLzc4fiU7YbtRrPZXHgld94pnTzZuj8zI23ZsvDnAIAlyBHRe5C9XNJOSf8ZEX/Ta3y9Xo9Go1G+iqeflt7yFunii6XzzmsF9WuvSc8919qzBoAlzvbeiKh3OjZR4pMt6Z8kHSwT0ouybp305S+3Arrt/POlVasq+XIAMEp6BrWkayT9rqTHbe8vPvanEfGVvlWxYoW0aVPfng4AlpKeQR0R35TkAdQCAOiAMxMBIDmCGgCSI6gBIDmCGgCSI6gBILlSJ7ws+EntpqTFngO+RtLzfSxnmJbKXJhHLswjn37M5RciotbpQCVBfS5sN7qdnTNqlspcmEcuzCOfqufC1gcAJEdQA0ByGYN667AL6KOlMhfmkQvzyKfSuaTbowYA/LSMHTUAYBaCGgCSG1pQ2/5n28dtP9HluG3/ne1Dth+zffWgayyjxDzeYfsl2/uLW8oLQpa52vworEnJeaRfE9sX2P6W7QPFPD7eYcwK218o1mNPcam8VErO41bbzVnr8QfDqLUM28ts77O9s8Ox6tYjIoZyk3StpKslPdHl+G9J+qpaf2J1o6Q9w6r1HOfxDkk7h11niXmslXR1cf8Nkv5H0mWjtiYl55F+TYp/44uL+8vVuk7pxjlj3ifpnuL+ZklfGHbdi5zHrZL+Ydi1lpzPH0n6XKf/f6pcj6F11BHxiKQfzTPkJkn/Gi3/JWmV7bWDqa68EvMYCVHuavPp16TkPNIr/o1fKR4uL25zX/m/SdJ9xf1tkq4vrsiURsl5jATb6yS9U9K9XYZUth6Z96gvlfT9WY+PagS/4QpvL371+6rtXxp2Mb3Mc7X5kVqTeeYhjcCaFL9m75d0XNLDEdF1PSJiWtJLkt442Cp7KzEPSXp3sZ22zfabBlxiWZ+WdIek012OV7YemYN6qXhUrXP4r5D095L+fcj1zKvX1eZHRY95jMSaRMRMRFwpaZ2kDbYvH3ZNi1FiHv8haTIi3ibpYf2kK03D9rskHY+IvcP4+pmD+pik2T9Z1xUfGykR8XL7V79oXWdyue2Ul1Yvrjb/JUmfjYjtHYaMxJr0mscorYkkRcSLknZLunHOoTPrYXtC0iWSfjjY6srrNo+I+GFEnCwe3ivplwddWwnXSNpk+4ikz0u6zvZn5oypbD0yB/UOSb9XvNNgo6SXIuLZYRe1ULZ/rr1PZXuDWv/m6b6ZSl5tPv2alJnHKKyJ7ZrtVcX9CyXdIOmpOcN2SPr94v7NknZF8UpWFmXmMed1jk1qva6QSkR8NCLWRcSkWi8U7oqIW+YMq2w9ylyFvBK271fr1fc1to9K+jO1XmhQRNwj6StqvcvgkKRXJb1nOJXOr8Q8bpZ0m+1pSa9J2pztm6nQ8WrzktZLI7UmZeYxCmuyVtJ9tpep9YPkixGx0/ZfSGpExA61fiD9m+1Dar2gvXl45XZVZh4ftL1J0rRa87h1aNUu0KDWg1PIASC5zFsfAAAR1ACQHkENAMkR1ACQHEENAMkR1ACQHEENAMn9P3dq/tkKbFkMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter([1,2,3,4],[2,3,4,8], s= [20,40,80,300],color = ['r','g','b','cyan'], marker='^')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f953826b1f0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter([1,2,3,4],[2,3,4,8], s= [20,40,80,300],color = ['r','g','b','cyan'], marker='*')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "male_hegiht = np.random.uniform(140, 200, size = 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([146.76919165, 188.42754857, 144.5349758 , 159.5514666 ,\n",
       "       143.70170327, 188.36196392, 158.22851829, 158.83115807,\n",
       "       181.27007651, 165.62944205, 144.86746292, 192.13975167,\n",
       "       162.26939379, 169.51201123, 145.44659957, 167.10469478,\n",
       "       146.89831792, 179.04343921, 176.93507458, 172.55027625])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "male_hegiht"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "male_id = np.arange(1,21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "male_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "male_hegiht = male_hegiht.reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "male_id = male_id.reshape(-1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "male = np.concatenate((male_id, male_hegiht), axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1.        , 146.76919165],\n",
       "       [  2.        , 188.42754857],\n",
       "       [  3.        , 144.5349758 ],\n",
       "       [  4.        , 159.5514666 ],\n",
       "       [  5.        , 143.70170327],\n",
       "       [  6.        , 188.36196392],\n",
       "       [  7.        , 158.22851829],\n",
       "       [  8.        , 158.83115807],\n",
       "       [  9.        , 181.27007651],\n",
       "       [ 10.        , 165.62944205],\n",
       "       [ 11.        , 144.86746292],\n",
       "       [ 12.        , 192.13975167],\n",
       "       [ 13.        , 162.26939379],\n",
       "       [ 14.        , 169.51201123],\n",
       "       [ 15.        , 145.44659957],\n",
       "       [ 16.        , 167.10469478],\n",
       "       [ 17.        , 146.89831792],\n",
       "       [ 18.        , 179.04343921],\n",
       "       [ 19.        , 176.93507458],\n",
       "       [ 20.        , 172.55027625]])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "male"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1.        , 169.40554661],\n",
       "       [  2.        , 141.86221782],\n",
       "       [  3.        , 146.48568816],\n",
       "       [  4.        , 168.17607521],\n",
       "       [  5.        , 176.48965287],\n",
       "       [  6.        , 155.62961662],\n",
       "       [  7.        , 142.48271431],\n",
       "       [  8.        , 155.07972853],\n",
       "       [  9.        , 147.68339344],\n",
       "       [ 10.        , 145.28779336],\n",
       "       [ 11.        , 176.54282806],\n",
       "       [ 12.        , 155.74047487],\n",
       "       [ 13.        , 147.74687859],\n",
       "       [ 14.        , 179.98931206],\n",
       "       [ 15.        , 161.42490851],\n",
       "       [ 16.        , 169.86355745],\n",
       "       [ 17.        , 157.9445894 ],\n",
       "       [ 18.        , 183.91450947],\n",
       "       [ 19.        , 141.03628818],\n",
       "       [ 20.        , 158.76134511]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "female = np.concatenate(( np.arange(1, 21).reshape(-1,1), np.random.uniform(140, 185, 20).reshape(-1,1)),axis = 1)\n",
    "female"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1.        , 146.76919165],\n",
       "       [  2.        , 188.42754857],\n",
       "       [  3.        , 144.5349758 ],\n",
       "       [  4.        , 159.5514666 ],\n",
       "       [  5.        , 143.70170327],\n",
       "       [  6.        , 188.36196392],\n",
       "       [  7.        , 158.22851829],\n",
       "       [  8.        , 158.83115807],\n",
       "       [  9.        , 181.27007651],\n",
       "       [ 10.        , 165.62944205],\n",
       "       [ 11.        , 144.86746292],\n",
       "       [ 12.        , 192.13975167],\n",
       "       [ 13.        , 162.26939379],\n",
       "       [ 14.        , 169.51201123],\n",
       "       [ 15.        , 145.44659957],\n",
       "       [ 16.        , 167.10469478],\n",
       "       [ 17.        , 146.89831792],\n",
       "       [ 18.        , 179.04343921],\n",
       "       [ 19.        , 176.93507458],\n",
       "       [ 20.        , 172.55027625],\n",
       "       [  1.        , 169.40554661],\n",
       "       [  2.        , 141.86221782],\n",
       "       [  3.        , 146.48568816],\n",
       "       [  4.        , 168.17607521],\n",
       "       [  5.        , 176.48965287],\n",
       "       [  6.        , 155.62961662],\n",
       "       [  7.        , 142.48271431],\n",
       "       [  8.        , 155.07972853],\n",
       "       [  9.        , 147.68339344],\n",
       "       [ 10.        , 145.28779336],\n",
       "       [ 11.        , 176.54282806],\n",
       "       [ 12.        , 155.74047487],\n",
       "       [ 13.        , 147.74687859],\n",
       "       [ 14.        , 179.98931206],\n",
       "       [ 15.        , 161.42490851],\n",
       "       [ 16.        , 169.86355745],\n",
       "       [ 17.        , 157.9445894 ],\n",
       "       [ 18.        , 183.91450947],\n",
       "       [ 19.        , 141.03628818],\n",
       "       [ 20.        , 158.76134511]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = np.concatenate((male,female))\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
       "       1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y = np.concatenate((np.ones(20), np.zeros(20)))\n",
    "Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f953718b310>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X[Y==1,0], X[Y==1,1],color= 'r')\n",
    "plt.scatter(X[Y==0,0], X[Y==0,1],color= 'g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9536c9a220>]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(10)\n",
    "y = np.random.random(size = 10)\n",
    "plt.plot(x, y, marker = 'x', linestyle='--')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9536c29580>]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, 'x--b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.1010101 ,  0.2020202 ,  0.3030303 ,  0.4040404 ,\n",
       "        0.50505051,  0.60606061,  0.70707071,  0.80808081,  0.90909091,\n",
       "        1.01010101,  1.11111111,  1.21212121,  1.31313131,  1.41414141,\n",
       "        1.51515152,  1.61616162,  1.71717172,  1.81818182,  1.91919192,\n",
       "        2.02020202,  2.12121212,  2.22222222,  2.32323232,  2.42424242,\n",
       "        2.52525253,  2.62626263,  2.72727273,  2.82828283,  2.92929293,\n",
       "        3.03030303,  3.13131313,  3.23232323,  3.33333333,  3.43434343,\n",
       "        3.53535354,  3.63636364,  3.73737374,  3.83838384,  3.93939394,\n",
       "        4.04040404,  4.14141414,  4.24242424,  4.34343434,  4.44444444,\n",
       "        4.54545455,  4.64646465,  4.74747475,  4.84848485,  4.94949495,\n",
       "        5.05050505,  5.15151515,  5.25252525,  5.35353535,  5.45454545,\n",
       "        5.55555556,  5.65656566,  5.75757576,  5.85858586,  5.95959596,\n",
       "        6.06060606,  6.16161616,  6.26262626,  6.36363636,  6.46464646,\n",
       "        6.56565657,  6.66666667,  6.76767677,  6.86868687,  6.96969697,\n",
       "        7.07070707,  7.17171717,  7.27272727,  7.37373737,  7.47474747,\n",
       "        7.57575758,  7.67676768,  7.77777778,  7.87878788,  7.97979798,\n",
       "        8.08080808,  8.18181818,  8.28282828,  8.38383838,  8.48484848,\n",
       "        8.58585859,  8.68686869,  8.78787879,  8.88888889,  8.98989899,\n",
       "        9.09090909,  9.19191919,  9.29292929,  9.39393939,  9.49494949,\n",
       "        9.5959596 ,  9.6969697 ,  9.7979798 ,  9.8989899 , 10.        ])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.linspace(0, 10,100)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.1 +0.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1111111111111111"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1/9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.41000000000000003"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.1 + 0.31"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9536e4d550>]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = np.sin(x)\n",
    "plt.plot(x, y)\n",
    "plt.plot(x, np.cos(x), 'y--')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f95380a4130>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, label= 'sin')\n",
    "plt.plot(x, np.cos(x), 'y--', label = 'cos')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-5, 15, -2, 2]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, label= 'sin')\n",
    "plt.plot(x, np.cos(x), 'y--', label = 'cos')\n",
    "plt.legend()\n",
    "plt.axis([-5,15, -2,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Q1', 'Q2', 'Q3', 'Q4']"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = [\"Q\"+ str(i) for i in range(1,5)]\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 4 artists>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = [10,20, 30, 60]\n",
    "plt.bar(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(x, y)\n",
    "plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rect = plt.bar(x, y)\n",
    "plt.grid(True)\n",
    "for index, item in enumerate(rect):\n",
    "    _x = item.get_x() + 0.3\n",
    "    _y = item.get_height() + 0.8\n",
    "    plt.text(_x, _y, y[index])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(y, labels=x, autopct=\"%2.f%%\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.axes(aspect = 1)\n",
    "plt.pie(y, labels=x, autopct=\"%2.f%%\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(y, labels=x, autopct=\"%2.f%%\", explode = (0.2, 0,0,0))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([31., 36., 63., 50., 49., 29., 14.,  9.,  2.,  1.]),\n",
       " array([ 4093.41180186,  5623.63876622,  7153.86573057,  8684.09269493,\n",
       "        10214.31965929, 11744.54662365, 13274.77358801, 14805.00055236,\n",
       "        16335.22751672, 17865.45448108, 19395.68144544]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(100)\n",
    "y = np.random.normal(9000, 3000, size = 300)\n",
    "y = y[y>=4000]\n",
    "plt.hist(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(y, bins = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x7f953634ef10>,\n",
       "  <matplotlib.lines.Line2D at 0x7f953634e4f0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x7f953637e820>,\n",
       "  <matplotlib.lines.Line2D at 0x7f953637e550>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x7f953634eeb0>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x7f9536384850>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x7f953634ec10>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.random.normal(size = 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.concatenate([data,[4,7,8,9, -4]])\n",
    "plt.boxplot(data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
